numpy.ma.dot

numpy.ma.dot(a, b, strict=False)

Return the dot product of two arrays.

Note

Works only with 2-D arrays at the moment.

This function is the equivalent of numpy.dot that takes masked values into account, see numpy.dot for details.

Parameters:

a, b : ndarray

Inputs arrays.

strict : bool, optional

Whether masked data are propagated (True) or set to 0 (False) for the computation. Default is False. Propagating the mask means that if a masked value appears in a row or column, the whole row or column is considered masked.

See also

numpy.dot

Equivalent function for ndarrays.

Examples

>>> a = ma.array([[1, 2, 3], [4, 5, 6]], mask=[[1, 0, 0], [0, 0, 0]])
>>> b = ma.array([[1, 2], [3, 4], [5, 6]], mask=[[1, 0], [0, 0], [0, 0]])
>>> np.ma.dot(a, b)
masked_array(data =
 [[21 26]
 [45 64]],
             mask =
 [[False False]
 [False False]],
       fill_value = 999999)
>>> np.ma.dot(a, b, strict=True)
masked_array(data =
 [[-- --]
 [-- 64]],
             mask =
 [[ True  True]
 [ True False]],
       fill_value = 999999)